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研究生：	余孝緯 Yu, Shiao-Wei
論文名稱：	共平面放射治療模擬系統 The Simulation System of Co-planar Radiotherapy
指導教授：	鄭國順 Cheng, Kuo-Sheng
學位類別：	碩士 Master
系所名稱：	工學院 - 醫學工程研究所 Institute of Biomedical Engineering
論文出版年：	2002
畢業學年度：	90
語文別：	英文
論文頁數：	61
中文關鍵詞：	反向治療、最佳化、遺傳基因演算法
外文關鍵詞：	Genetic algorithm, Optimization, Inverse treatment planning
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　　本研究是發展以醫用直線加速器殺死腫瘤細胞且正常組織受到的傷害最小的技術，以解決傳統正向治療中，常面臨無法將治療射束完全限制在腫瘤體積範圍內的問題。目前研究的目的是依據反向治療之觀念(Inverse treatment planning)配合遺傳基因演算法(Genetic algorithm)找出最佳的放射擺設位置。之後建立一套電腦模擬劑量計算系統與發展圖形化使用者介面(GUI)，計算出腫瘤區域與劑量涵蓋範圍與相關性，最終算出最佳化(Optimization)擺設位置與劑量吸收情形。本研究已建立二維放射線劑量計算模式，延伸至三維模擬治療系統劑量模式。

　　The goal of radiation dosage distribution profiles is to deliver a high dose target volumes and reduce damage for the surrounding healthy tissues. In traditional, the forward methods are applied to establish the dose distributions. It is a kind of trial-and-error method to waste a lot of time, however, maybe cannot find the optimal solution. In order to more increase the accuracy of dose computation, the inverse models are introduced in this study to find and solve the optimization beam angles and positions. The GA-based computerized software with a 2D graphic-user-interface has been developed to solve the optimization problem and to control the beams positions that replace the manual arranged beam positions in radiotherapy treatment planning.

CONTENTS
ABSTRACTS………………………………………………………………………..Ⅰ
CONTENTS…………………………………………………………………………Ⅳ
ACKNOWLEDGMENT……………………………………………………………Ⅲ
LIST OF TABLES…………………………………………………………………..Ⅵ
LIST OF FIGURES………………………………………………………………Ⅶ

CHAPTER  1  Introduction 
　　1.1  Background……………………………………………………………...1
　　1.2  Literature Review……………………………………………………….6
　　　　1.2.1 Inverse planning method ………………………………………...7
　　1.3  Motivation……………………………………………………………….8
　　1.4  Purposes ………………………………………………………………..9

CHAPTER  2  Methods
　　2.1  CT image preprocessing ………………………………………………12
　　　　2.1.1 Definition the tumor counter and body contour………………...12
　　　　　　2.1.1.1 Median filter …………………………………………...13
　　　　　　2.1.1.2 Otsu method ……………………………………………14
　　　　　　2.2.1.3 Edge Detection (Sobel operator) ………………………15
　　　　　　2.2.1.4 Image merge ……………………………………………16 
　　2.2 The Physical Principle……………………………………………………17 
　　　　2.2.1 Radiation absorbed dose………………………………………….17
　　2.3 Collection the Dose Data…………………………………………………19
　　　　2.3.1 Dependence on Source Surface Distance (SSD) …………………20
Ⅳ
　　2.4 Calculation the Dose Distribution Profile………………………………...20
　　　　2.4.1 Computerized beam orientation and position……………….20
　　2.5 Genetic Algorithm……………………………………………………..21
　　　　2.5.1 Selection the Parameters……………………………………….21
　　　　2.5.2 Parameters Representation……………………………………..22
　　　　2.5.3 Natural Selection………………………………………………23
　　　　　　2.5.3.1 Tournament Selection…………………………………23
　　　　　　2.5.3.2 Roulette Wheel Selection……………………………...24
　　　　2.5.4 Fitness Function………………………………………………. 24
　　　　2.5.5 Reproduction …………………………………………………..25
　　　　2.5.6 Crossover ………………………………………………………26
　　　　2.5.7 Mutation ……………………………………………………….26

CHAPTER  3  Results and Discussion
　　3.1 Definition the tumor contour ……………………………………………29
　　　　3.1.1 The image preprocessing………………………………………29
　　3.2 Definition the Brain Edge Contour……………………………………... 30
　　3.3 Establish 2D Absorption Dose Distribution …………………………….31
　　3.4 Two-Dimensional Dose Display techniques……………………………..37
　　3.5 Simulation Phantom and Genetic Algorithm ……………………………37
　　3.6 Clinical Test 1: Brain Tumor …………………………………………….40
　　3.7 Clinical Test 2: Liver Tumor …………………………………………….47
　　3.8 Three-Dimensional Reconstruction and Visualization………………..….50
　　3.9 Discussion………………………………………………………………..52

Ⅴ
CHAPTER 4 Conclusion and Prospects………………………..54
　　4.1 Prospect…………………………………………………………………..55
　　　　4.1.1 Adaptive searching techniques and mixed encoding scheme………… 55
　　　　4.1.2 Volume visualization in beam targeting ………….……………………56

REFERENCES ……………………………………………………..57
                                    

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校內：2101-08-22公開
校外：2101-08-22公開電子論文尚未授權公開，紙本請查館藏目錄

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